Meta‐analysis of microRNA expression in lung cancer

The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the application of different technological platforms and small sample size, the miRNA expression profiling efforts have led to inconsistent result...

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Veröffentlicht in:	International journal of cancer Jg. 132; H. 12; S. 2884 - 2893
Hauptverfasser:	Võsa, Urmo, Vooder, Tõnu, Kolde, Raivo, Vilo, Jaak, Metspalu, Andres, Annilo, Tarmo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken Wiley Subscription Services, Inc., A Wiley Company 15.06.2013 Wiley-Blackwell Wiley Subscription Services, Inc
Schlagworte:	Biological and medical sciences Biomarkers, Tumor Cancer Cluster Analysis Gene Expression Profiling Gene Expression Regulation, Neoplastic gene set enrichment analysis Humans Lung cancer Lung Neoplasms - genetics Lung Neoplasms - metabolism Medical research Medical sciences Meta-analysis microRNA MicroRNAs MicroRNAs - genetics Multiple tumors. Solid tumors. Tumors in childhood (general aspects) Pneumology Signal Transduction Tumors Tumors of the respiratory system and mediastinum Human Lung disease RNA interference Respiratory disease Lung cancer Evidence-based practice Micro RNA meta-analysis Malignant tumor Evidence-based medicine Metaanalysis Gene silencing Cancerology Gene Genetics Bronchus disease microRNA gene set enrichment analysis Cancer
ISSN:	0020-7136, 1097-0215, 1097-0215
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Abstract	The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the application of different technological platforms and small sample size, the miRNA expression profiling efforts have led to inconsistent results between the studies. We performed a comprehensive meta‐analysis of 20 published miRNA expression studies in lung cancer, including a total of 598 tumor and 528 non‐cancerous control samples. Using a recently published robust rank aggregation method, we identified a statistically significant miRNA meta‐signature of seven upregulated (miR‐21, miR‐210, miR‐182, miR‐31, miR‐200b, miR‐205 and miR‐183) and eight downregulated (miR‐126‐3p, miR‐30a, miR‐30d, miR‐486‐5p, miR‐451a, miR‐126‐5p, miR‐143 and miR‐145) miRNAs. We conducted a gene set enrichment analysis to identify pathways that are most strongly affected by altered expression of these miRNAs. We found that meta‐signature miRNAs cooperatively target functionally related and biologically relevant genes in signaling and developmental pathways. We have shown that such meta‐analysis approach is suitable and effective solution for identification of statistically significant miRNA meta‐signature by combining several miRNA expression studies. This method allows the analysis of data produced by different technological platforms that cannot be otherwise directly compared or in the case when raw data are unavailable. What's new? The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the application of different technological platforms and small sample size, the miRNA expression profiling efforts have led to inconsistent results. Using a meta‐analysis of more than 1100 lung cancer and non‐cancerous samples from 20 original studies, here the authors have identified a meta‐signature of seven up‐ and eight down‐regulated miRNAs. Their analysis highlights the challenges related with the development of miRNA‐based tests and emphasizes the need for rigorous evaluation of the results before proceeding to clinical trials.
AbstractList	The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the application of different technological platforms and small sample size, the miRNA expression profiling efforts have led to inconsistent results between the studies. We performed a comprehensive meta-analysis of 20 published miRNA expression studies in lung cancer, including a total of 598 tumor and 528 non-cancerous control samples. Using a recently published robust rank aggregation method, we identified a statistically significant miRNA meta-signature of seven upregulated (miR-21, miR-210, miR-182, miR-31, miR-200b, miR-205 and miR-183) and eight downregulated (miR-126-3p, miR-30a, miR-30d, miR-486-5p, miR-451a, miR-126-5p, miR-143 and miR-145) miRNAs. We conducted a gene set enrichment analysis to identify pathways that are most strongly affected by altered expression of these miRNAs. We found that meta-signature miRNAs cooperatively target functionally related and biologically relevant genes in signaling and developmental pathways. We have shown that such meta-analysis approach is suitable and effective solution for identification of statistically significant miRNA meta-signature by combining several miRNA expression studies. This method allows the analysis of data produced by different technological platforms that cannot be otherwise directly compared or in the case when raw data are unavailable.The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the application of different technological platforms and small sample size, the miRNA expression profiling efforts have led to inconsistent results between the studies. We performed a comprehensive meta-analysis of 20 published miRNA expression studies in lung cancer, including a total of 598 tumor and 528 non-cancerous control samples. Using a recently published robust rank aggregation method, we identified a statistically significant miRNA meta-signature of seven upregulated (miR-21, miR-210, miR-182, miR-31, miR-200b, miR-205 and miR-183) and eight downregulated (miR-126-3p, miR-30a, miR-30d, miR-486-5p, miR-451a, miR-126-5p, miR-143 and miR-145) miRNAs. We conducted a gene set enrichment analysis to identify pathways that are most strongly affected by altered expression of these miRNAs. We found that meta-signature miRNAs cooperatively target functionally related and biologically relevant genes in signaling and developmental pathways. We have shown that such meta-analysis approach is suitable and effective solution for identification of statistically significant miRNA meta-signature by combining several miRNA expression studies. This method allows the analysis of data produced by different technological platforms that cannot be otherwise directly compared or in the case when raw data are unavailable. The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the application of different technological platforms and small sample size, the miRNA expression profiling efforts have led to inconsistent results between the studies. We performed a comprehensive meta-analysis of 20 published miRNA expression studies in lung cancer, including a total of 598 tumor and 528 non-cancerous control samples. Using a recently published robust rank aggregation method, we identified a statistically significant miRNA meta-signature of seven upregulated (miR-21, miR-210, miR-182, miR-31, miR-200b, miR-205 and miR-183) and eight downregulated (miR-126-3p, miR-30a, miR-30d, miR-486-5p, miR-451a, miR-126-5p, miR-143 and miR-145) miRNAs. We conducted a gene set enrichment analysis to identify pathways that are most strongly affected by altered expression of these miRNAs. We found that meta-signature miRNAs cooperatively target functionally related and biologically relevant genes in signaling and developmental pathways. We have shown that such meta-analysis approach is suitable and effective solution for identification of statistically significant miRNA meta-signature by combining several miRNA expression studies. This method allows the analysis of data produced by different technological platforms that cannot be otherwise directly compared or in the case when raw data are unavailable. What's new? The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the application of different technological platforms and small sample size, the miRNA expression profiling efforts have led to inconsistent results. Using a meta-analysis of more than 1100 lung cancer and non-cancerous samples from 20 original studies, here the authors have identified a meta-signature of seven up- and eight down-regulated miRNAs. Their analysis highlights the challenges related with the development of miRNA-based tests and emphasizes the need for rigorous evaluation of the results before proceeding to clinical trials. [PUBLICATION ABSTRACT] The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the application of different technological platforms and small sample size, the miRNA expression profiling efforts have led to inconsistent results between the studies. We performed a comprehensive meta‐analysis of 20 published miRNA expression studies in lung cancer, including a total of 598 tumor and 528 non‐cancerous control samples. Using a recently published robust rank aggregation method, we identified a statistically significant miRNA meta‐signature of seven upregulated (miR‐21, miR‐210, miR‐182, miR‐31, miR‐200b, miR‐205 and miR‐183) and eight downregulated (miR‐126‐3p, miR‐30a, miR‐30d, miR‐486‐5p, miR‐451a, miR‐126‐5p, miR‐143 and miR‐145) miRNAs. We conducted a gene set enrichment analysis to identify pathways that are most strongly affected by altered expression of these miRNAs. We found that meta‐signature miRNAs cooperatively target functionally related and biologically relevant genes in signaling and developmental pathways. We have shown that such meta‐analysis approach is suitable and effective solution for identification of statistically significant miRNA meta‐signature by combining several miRNA expression studies. This method allows the analysis of data produced by different technological platforms that cannot be otherwise directly compared or in the case when raw data are unavailable. What's new? The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the application of different technological platforms and small sample size, the miRNA expression profiling efforts have led to inconsistent results. Using a meta‐analysis of more than 1100 lung cancer and non‐cancerous samples from 20 original studies, here the authors have identified a meta‐signature of seven up‐ and eight down‐regulated miRNAs. Their analysis highlights the challenges related with the development of miRNA‐based tests and emphasizes the need for rigorous evaluation of the results before proceeding to clinical trials. The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the application of different technological platforms and small sample size, the miRNA expression profiling efforts have led to inconsistent results between the studies. We performed a comprehensive meta-analysis of 20 published miRNA expression studies in lung cancer, including a total of 598 tumor and 528 non-cancerous control samples. Using a recently published robust rank aggregation method, we identified a statistically significant miRNA meta-signature of seven upregulated (miR-21, miR-210, miR-182, miR-31, miR-200b, miR-205 and miR-183) and eight downregulated (miR-126-3p, miR-30a, miR-30d, miR-486-5p, miR-451a, miR-126-5p, miR-143 and miR-145) miRNAs. We conducted a gene set enrichment analysis to identify pathways that are most strongly affected by altered expression of these miRNAs. We found that meta-signature miRNAs cooperatively target functionally related and biologically relevant genes in signaling and developmental pathways. We have shown that such meta-analysis approach is suitable and effective solution for identification of statistically significant miRNA meta-signature by combining several miRNA expression studies. This method allows the analysis of data produced by different technological platforms that cannot be otherwise directly compared or in the case when raw data are unavailable.
Author	Vilo, Jaak Annilo, Tarmo Võsa, Urmo Vooder, Tõnu Kolde, Raivo Metspalu, Andres
Author_xml	– sequence: 1 givenname: Urmo surname: Võsa fullname: Võsa, Urmo – sequence: 2 givenname: Tõnu surname: Vooder fullname: Vooder, Tõnu – sequence: 3 givenname: Raivo surname: Kolde fullname: Kolde, Raivo – sequence: 4 givenname: Jaak surname: Vilo fullname: Vilo, Jaak – sequence: 5 givenname: Andres surname: Metspalu fullname: Metspalu, Andres – sequence: 6 givenname: Tarmo surname: Annilo fullname: Annilo, Tarmo email: tarmo.annilo@ut.ee
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Keywords	Human Lung disease RNA interference Respiratory disease Lung cancer Evidence-based practice Micro RNA meta-analysis Malignant tumor Evidence-based medicine Metaanalysis Gene silencing Cancerology Gene Genetics Bronchus disease microRNA gene set enrichment analysis Cancer
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Notes	UV carried out data analysis and drafted the manuscript, TV participated in data collection and analysis, RK and JV helped to design the study and analyze the data, AM participated in the design of the study and helped to draft the manuscript, TA conceived of the study, and participated in its design and coordination and drafted the manuscript. All authors read and approved the final manuscript. Conflict of interest: The authors declare that they have no competing interests. Tel.: +372‐737‐5882, Fax: +372‐742‐0286 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
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Snippet	The prognostic and diagnostic value of microRNA (miRNA) expression aberrations in lung cancer has been studied intensely in recent years. However, due to the...
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SubjectTerms	Biological and medical sciences Biomarkers, Tumor Cancer Cluster Analysis Gene Expression Profiling Gene Expression Regulation, Neoplastic gene set enrichment analysis Humans Lung cancer Lung Neoplasms - genetics Lung Neoplasms - metabolism Medical research Medical sciences Meta-analysis microRNA MicroRNAs MicroRNAs - genetics Multiple tumors. Solid tumors. Tumors in childhood (general aspects) Pneumology Signal Transduction Tumors Tumors of the respiratory system and mediastinum
Title	Meta‐analysis of microRNA expression in lung cancer
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